Artificial Neural Networks – ICANN 2010

20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part III

  • Konstantinos Diamantaras
  • Wlodek Duch
  • Lazaros S. Iliadis

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6354)

Table of contents

  1. Front Matter
  2. Classification – Pattern Recognition

    1. Iago Porto-Díaz, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Óscar Fontenla-Romero
      Pages 11-20
    2. Yakov Karandashev, Boris Kryzhanovsky, Leonid Litinskii
      Pages 41-51
    3. Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth
      Pages 52-61
    4. Urs Bergmann, Christoph von der Malsburg
      Pages 72-81
    5. Dominik Scherer, Andreas Müller, Sven Behnke
      Pages 92-101
    6. Hiroaki Hasegawa, Masafumi Hagiwara
      Pages 102-105
    7. Antonio García-Manso, Carlos J. García-Orellana, Horacio M. González-Velasco, Miguel Macías-Macías, Ramón Gallardo-Caballero
      Pages 106-109
    8. Roman Záluský, Emil Raschman, Mário Krajmer, Daniela Ďuračková
      Pages 114-117
    9. Jun Wu, Xin Wang, Xiaodong Lee, Baoping Yan
      Pages 118-123
    10. Mateusz Kobos, Jacek Mańdziuk
      Pages 124-129
    11. Achilleas Zapranis, Prodromos Tsinaslanidis
      Pages 130-136
    12. Araken M. Santos, Laura E. A. Santana, Anne M. Canuto
      Pages 137-142
    13. Rikke Amilde Løvlid, Pinar Öztürk
      Pages 143-148

Other volumes

  1. 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part I
  2. 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part II
  3. Artificial Neural Networks – ICANN 2010
    20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part III

About these proceedings

Introduction

th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15–18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the ?eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito?eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti?cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexcite or inhibit the signal being communicated. ANNs have the ability “to learn” by example (a large volume of cases) through several iterations without requiring a priori ?xed knowledge of the relationships between process parameters.

Keywords

adaptive algorithms algorithms ants architectures artificial intelligence brain-computer interfaces classification complexity computational intelligence computational neuroscience data mining evolutionary algorithms expectation–maximization algorithm object recognition pattern recognition

Editors and affiliations

  • Konstantinos Diamantaras
    • 1
  • Wlodek Duch
    • 2
  • Lazaros S. Iliadis
    • 3
  1. 1.Department of InformaticsTEI of ThessalonikiSindosGreece
  2. 2.Department of InformaticsNicolaus Copernicus University, School of Physics, Astronomy, and InformaticsTorunPoland
  3. 3.Department of Forestry and Management of the Environment and Natural ResourcesDemocritus University of ThraceOrestiada ThraceGreece

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-15825-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-15824-7
  • Online ISBN 978-3-642-15825-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book